class_docstr: Compute peak fft bins (int), and their magnitudes' value (float), to concatenate them.
  This is intended to be used only after a NumpyFFT absolute step.
  
  .. seealso::
      :class:`~neuraxle.base.BaseStep`,
      :class:`~neuraxle.base.NonFittableMixin`,
      :class:`~neuraxle.steps.numpy.NumpyFFT`,
      :class:`Cheap3DTo2DTransformer`
code: def __init__(self):
      super().__init__(
          [NumpyArgMax(axis=-2), NumpyMax(axis=-2)],
          joiner=NumpyConcatenateInnerFeatures(),
      )
  
file_path: Neuraxle/neuraxle/steps/features.py
imports: from neuraxle.pipeline import Pipeline
  from neuraxle.steps.flow import ChooseOneOrManyStepsOf
  from neuraxle.steps.numpy import NumpyFFT, NumpyAbs, NumpyFlattenDatum, NumpyConcatenateInnerFeatures, NumpyMean, NumpyMedian, NumpyMin, NumpyMax, NumpyArgMax
  from neuraxle.union import FeatureUnion
label_desc: Use image node_id 1 to create a new FFTPeakBinWithValue object from inherited base classes: FeatureUnion with example: obj = FFTPeakBinWithValue()